One or more aspects relate to predicting future utilization of a resource.
Predictive analytics and predictive forecasting are currently hot themes in the field of business intelligence or business analytics. They may be used to forecast revenue numbers or business results based on historic transaction data. However, the same technology may be used in systems for predictive maintenance and preventive customer service actions. The technology may also be used for forecasting potential bottlenecks in respect to computing resources, e.g., at the end of the calculation period when a large amount of consolidation calculations have to be made. All of these predictive systems have in common that an extrapolation in time is performed for a resource in question based on a historic real use of the resource in question.
There are several disclosures related to predicting utilization of a resource.
Document US 2012/0173477 A1, which is hereby incorporated by reference herein in its entirety, discloses systems and methods to monitor database system resource consumption over various time periods, in conjunction with scheduled data loading, data export and clearing operations. The additional activities may include generating a database system resource consumption map based on the monitoring, and digesting database system workload throttling to accommodate predictive database system resource consumption based on the resource consumption map and current system loading, prior to the current database resource consumption reaching a predefined critical consumption level.
Another document, US 2014/0006609 A1, which is hereby incorporated by reference herein in its entirety, is proposing a method for optimizing future resource usage in the cloud environment including first and second cloud services. Each cloud service is associated with at least one of technical and business restrictions defining a maximum capacity.
Document US 2013/0066646 A1, which is hereby incorporated by reference herein in its entirety, discloses a system configuration and techniques for optimizing schedules and associated use predictions of a multiple resource planning workflow. It may be applicable to environments, such as radiologist scheduling in a tele-radiology workflow, and may also provide forecasting and the generation of customized recommendations for scheduling and other resource scenarios. The forecast may be enhanced through the use of historical data models and estimated future data models.
It may be noted that the mentioned methods and systems rely on historic transactions actually making use of the resource. This may be equivalent to predicting future revenue numbers based on historic revenue numbers.